Nicola Altini

Assistant Professor in Bioengineering

Polytechnic University of Bari

Italy

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About

Nicola Altini is an Assistant Professor in Bioengineering at the Polytechnic University of Bari, Italy. His research interests encompass pharmacometrics, digital twin modeling, multimodal imaging, and artificial intelligence applications in medical diagnostics. Recent publications include work on adaptive therapy scheduling in advanced gastric cancer, deep learning for brain structure segmentation, and mechanisms linking pathomics to pancreatic cancer mutations.

Articles (10)

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2023

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2023

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2023

Collaborators (10)

Vitoantonio Bevilacqua

Polytechnic University of Bari

ITALY

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Massimo La Scala

Professor

Polytechnic University of Bari

ITALY

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Antonio Brunetti

Polytechnic University of Bari

ITALY

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Francesco Pesce

Chief

Fatebenefratelli Hospital

ITALY

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Jean-Baptiste Gibier

Université Lille 2 Droit et Santé

FRANCE

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Anibal Pedraza

Assistant Professor

University of Castilla-La Mancha

SPAIN

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Angela Ernst

University of Cologne

GERMANY

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Paola Pontrelli

Università degli Studi di Bari Aldo Moro Scuola di Medicina

ITALY

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Domenico Buongiorno

Polytechnic University of Bari

ITALY

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Samira Zare

University of Houston

UNITED STATES

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Nicola Altini

Research Interests

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About

Articles (10)

Permutation-Invariant Cascaded Attentional Set Operator for Computational Nephropathology

Pharmacometric and Digital Twin modeling for adaptive scheduling of combination therapy in advanced gastric cancer

A Comparison Between Unimodal and Multimodal Segmentation Models for Deep Brain Structures from T1- and T2-Weighted MRI

A multimodal framework for assessing the link between pathomics, transcriptomics, and pancreatic cancer mutations

Explainable Intelligent Inspection of Solar Photovoltaic Systems with Deep Transfer Learning: Considering Warmer Weather Effects Using Aerial Radiometric Infrared Thermography

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data

Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy

An Explainable Radiogenomic Framework to Predict Mutational Status of KRAS and EGFR in Lung Adenocarcinoma Patients

Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability

Collaborators (10)

Vitoantonio Bevilacqua

Massimo La Scala

Antonio Brunetti

Francesco Pesce

Jean-Baptiste Gibier

Anibal Pedraza

Angela Ernst

Paola Pontrelli

Domenico Buongiorno

Samira Zare

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